Alpha School has been on my mind lately, since I listened to this podcast. I don’t normally listen to that podcast, but I discovered it in my podcasts app. Joe Liemandt has some good insights and ideas, and the podcast serves mostly as marketing for Alpha School. .

Because I’m tuned into AI and education, I’ve had quite a few stories about Alpha School in my feeds. And then this Wired Story hit my feed, and it really made me think.

A few things stand out to me:

• The host’s child attended Alpha School and then left
• None of the results claimed are independently verified
• There’s always tradeoffs

It was a head scratcher to learn that Peter Attia’s child attended Alpha Schools but then left. If it was so good, why leave? The Wired story states that this is a common occurence since many parents find that Alpha Schools pushes their children too hard.

The fact that none of Alpha Schools claims are independently verified is also a red flag. With the market opportunity uncovered, there are many private schools making big claims to attract students. There are a lot of snake oil salesmen.

There are always tradeoffs. If students are learning everything they need to know in two hours with AI, then there is going to be a tradeoff. Alpha Schools may enable students to outperform their peers on MAP scores, but there has to be a tradeoff. If you believe the Wired story, it is the student’s wellbeing and sanity.

I asked Gemini to summarize an article I was looking at: Joseph Aoun’s Thoughts on Higher Education. Because it was behind a paywall, it declined to do so. However, it offered to look across the web and to create an outline based on other remarks that Dr. Aoun has made in the past. I thought the output was extremely useful, and I plan on using this approach more often.

Outline of Joseph Aoun’s Thoughts on Higher Education in America Today

I. The Context: Major Challenges and the Need for a New Social Compact

A. The Age of Artificial Intelligence (AI)

1. AI is the “fourth transformational force” in history (after fire, steam, and electricity).
2. It threatens to automate both low- and high-skilled labor (e.g., legal research, data analysis, medical image interpretation).
3. The rise of AI is making knowledge itself a commodity that can be easily accessed.
4. The purpose of education must shift from preparing students for their first job (which may disappear) to preparing them for life and multiple careers.

B. “Icebergs” Confronting Higher Education

1. Demographic Cliff: A nationwide trend of fewer high school graduates choosing to attend college.
2. Crisis of Trust: Society’s faith in the value of higher education is declining.
3. Fraying Social Compact: The post-World War II agreement between higher education and society (exchange of funding/non-profit status for educated citizens) is weakened and needs to be rebuilt.

II. The Proposed Solution: A New Educational Model—”Humanics”

A. Goal of a “Robot-Proof” Education

1. To cultivate a creative mindset and mental elasticity.
2. To teach mastery of content while developing uniquely human skills that machines cannot easily replicate.
3. To enable students to invent, discover, or create something society deems valuable.

B. The Three Core Literacies of Humanics

1. Data Literacy: The ability to read, manage, analyze, and drive insights from the flow of big data.
2. Technological Literacy: The ability to code, understand engineering principles, and know how machines work.
3. Human Literacy: The development of “soft skills” such as:
   • Communication and design
   • Understanding the humanities and context

C. The Essential Cognitive Capacities

1. Critical Thinking: The ability to analyze information objectively.
2. Systems Thinking: The capacity to view business, technology, and machines holistically and in an integrated manner.
3. Entrepreneurship: Applying a creative mindset to economic or business challenges.
4. Cultural Agility: The ability to adapt and function effectively across different cultures and contexts.

III. The Necessary Institutional Transformation

A. Emphasizing Experiential Learning

1. Co-operative education (co-op) and hands-on experience are more important than ever to hone human skills.
2. Learning in context (outside the classroom) is essential for integrating knowledge with real-world challenges.

B. Shifting to Lifelong Learning

1. Universities must broaden their reach beyond undergraduate and graduate students to become engines for continuous learning throughout a person’s life.
2. Educational offerings must be customized and personalized to meet the evolving needs of adult learners and employers.
3. The focus shifts from a single degree to providing continuous access to education over an entire lifetime.

C. The Global University Model

1. Developing a global network of campuses provides a broader perspective and student mobility.
2. This system allows a university to weather challenges and take advantage of opportunities in different markets.

I attended the Future of Higher Ed AI yesterday evening. The conversations were thought-provoking, and several quotes stuck with me long after the sessions ended.

“Simulations used to be faberge eggs, now they are real eggs.”

What was once rare, expensive, and carefully curated is now accessible and practical because of AI. One of the panelists spoke about a post-partum hemorrhage simulation with a chatbot that tests communication skills, complete with an AI debriefer. Faculty can see transcripts, track performance, and provide targeted feedback.

“I’m scared that education will be taken by Google U or Anthropic U.”

It’s a legitimate fear. As AI becomes more sophisticated, what’s stopping tech giants from creating their own educational institutions? What happens to traditional higher ed when anyone can access world-class AI tutors?

“Those grade reports … don’t feed into a continual improvement loop.”

“Grades do not provide meaningful feedback that lead to learning.”

“When you go to a doctor they don’t tell you pass/fail, they give you an overview of where your health is.”

We’ve built an entire system around pass/fail, A-F grades, but do they actually help students learn? Or do they just sort them into categories? Where is the feedback loop?

Other Highlights

Duet / SNHU showed how they’re using Google Meet transcripts with custom Gems to analyze student context, background, and mindset shifts. They’re connecting with systems like Salesforce to track student performance throughout the term.

Instructors are building their own AI agents since he can’t integrate them into Moodle or Canvas. They are also developing their own content because they can’t find suitable AI content elsewhere.

I built an AI-powered news aggregator using Cursor. It automatically finds and summarizes the latest education technology news every week.

How does it work?

The system runs on a schedule. Every Monday, it:

1. Fetches recent edtech articles from NewsAPI
2. Sends them to an AI model (Deepseek R1) for summarization
3. Formats the summaries into a clean, readable list
4. Updates the website automatically

The technology

NewsAPI - Finds relevant articles about education and edtech Deepseek R1 - An AI model that reads and summarizes the articles in natural language GitHub Actions - Runs the script automatically every week without manual intervention Python - The glue that connects everything together

Expected costs

The system is designed to be cost-effective. NewsAPI offers a free tier that covers basic usage. Deepseek R1 is significantly cheaper than other AI models like Llama 2 70B. Running weekly, the total monthly cost should be under $5. This makes it an affordable way to automate content curation without breaking the bank.

Why it matters

This experiment shows how AI can automate content curation. Instead of manually reading dozens of articles, the AI does the heavy lifting. It finds what’s important and presents it in a digestible format.

The system is fully automated. Once set up, it runs itself. This frees up time to focus on other work while staying informed about the latest trends in education technology.

Cursor really takes over. I’m not complaining, I’m just saying it really gets things done. If you ask it a question, you’d better be ready for it to start committing code.

Info to Implementation

I was having an issue with a news API pulling garbage. My prompt was purely informational. What search parameters does this API offer? I was trying to understand what options there were.

Cursor’s response?

1. First, it immediately gave me a perfect, itemized list of every parameter: qInTitle, domains, sortBy: popularity, etc. Exactly what I asked for.
2. Then, the takeover. It didn’t wait. It instantly transitioned from assistant to developer:
   • Let me update your configuration to get better, more focused results:
   • Now, let me update the Python script to use these new parameters:

It skips the “do you want me to do this?” step. It sees the goal—getting better results—and aggressively starts coding, testing, and debugging on its own:

• The query is too restrictive! Let me adjust it to be more practical:
• Let me try without the domains filter to see if that’s the issue:
• Great! It found 10 articles. Let me check the quality:
• Excellent! Much better results! Let me commit this change...

That is a five-minute debug and optimization cycle completed in about five seconds.

The Risks

This bias for action is why I pay for the tool. It’s fantastic.

But it also makes you manage it differently. You have to be precise. You have to narrow the context and set some limits. “Don’t implement this.” You have to understand that its default state is “go.”

This is the trade-off. I truly appreciate this quality of Cursor, but I also recognize that it can be risky, especially if you include too many commands in the allowlist.

Cursor is less an assistant and more a brilliant, relentless partner.

What I did

Today was a productive day. I worked with Cursor to implement a minimalist theme. It amazes me that it seemingly has an understanding of minimalist design. At one point I tried setting up a Google form instead of a different service, and Cursor commented that it didn’t look good with the minimalist theme.

Changes I made today

• Applied a minimalist theme
• Implemented a form using email.js